Richard Seroter, who leads developer experience at Google Cloud, describes Google’s full-stack AI approach as a deliberate strategy to deliver powerful, cost-efficient products to both expert developers and everyday users.
Who is Richard Seroter?
Seroter has worked for Google for about three years, leading developer relations and technical writing teams. His current responsibilities include product engineering for languages and frameworks, along with the Open Source Programs Office. The team builds programming languages and frameworks, meets directly with the community to share best practices, and crafts documentation. The ultimate goal is to give developers the confidence that they can get things done with Google products.
Where does the term full-stack come from?
The phrase originated in software development about a decade ago. Historically, building an application required multiple specialised teams. A front-end developer built user interfaces, a back-end developer handled server-side logic, and a dedicated database team managed data.
A full-stack engineer emerged to describe a developer who could work across all these functions independently. Instead of handing off components from one person to another, a full-stack engineer could take an idea from a rough concept all the way to a fully running piece of software.
How does this apply to AI?
Google has taken that end-to-end principle and applied it to artificial intelligence. If you are trying to deliver value with AI, you can either buy disparate parts from different vendors and try to stitch them together yourself, or you can look for an integrated system where everything is already connected.
An intentional AI stack needs a cohesive combination of layers to get a job done. These layers include compute infrastructure, an AI model, an orchestration platform, and the user interfaces.
Google has invested in every single layer. The company provides hardware like Tensor Processing Units (TPUs), frontier models developed by Google DeepMind like the Gemini family, the Gemini Enterprise Agent Platform, and interfaces people use daily, like Maps and Gmail. Google has essentially done the hunting for you and put all the necessary components right inside the box.
Was this a deliberate strategy?
It was absolutely a deliberate, decades-long strategy. For instance, the bet on custom TPUs is already over 10 years old. Google recognised early on that there is massive value in owning its own supply chain and raw infrastructure when serving up the world’s most important internet services.
Owning that thread throughout the entire stack lets Google deliver a level of service, performance and reliability that is very hard to achieve if you are at the mercy of multiple parties.
Does this limit builders?
Seroter says locking people in does not align with Google’s ethos. No company does open source quite like Google; the company regularly gives away foundational technology and source code that the entire industry depends on.
Google describes its AI platform as “opinionated but extensible” and “batteries included”. This means everything needed to build and run an application is ready to go out of the box. However, if you want to use another company’s AI model instead of Gemini, or hook up different software instead of Google Workspace, you can plug those right in.
The company wants you to use its products every day based on the completeness of the platform, not because it forced you into a closed choice.
What are the benefits?
Because Google manages the entire stack — literally from running the underlying infrastructure all the way up to delivering Gmail — there is massive system reliability. If a technical failure happens at one layer, Google’s ownership of the platform allows it to catch it and handle it at another layer easily, rather than waiting for an external provider to fix it.
There is also an economic advantage. Since Google is not paying third-party vendors for anything, customers do not have to absorb those fees, which means Google can offer remarkably competitive pricing.
How can I get started?
Google wants to make technology accessible to billions of people who do not have an engineering degree, so it provides clear front doors depending on what you are trying to achieve.
If you want to take a creative idea and quickly build a prototype web application, Google AI Studio is a place to start. You can build a prototype in just a few minutes and deploy it directly to Cloud Run — Google’s Cloud-based platform that runs apps — with the click of a single button.
If you are looking for a low-code option to automate your day-to-day work, try Gemini Enterprise Platform. You can build workflows to clean up your inbox or parse complex spreadsheets without ever having to write or even look at a single line of code.
For those looking to orchestrate more complex application or agent builds, the Antigravity platform is incredibly powerful. Its rich surfaces allow you to build sophisticated systems without requiring advanced programming knowledge.
Whatever you are trying to make and whatever level of developer skill you have, there is a Google full-stack tool ready to help you.
What it means
Builders no longer need to hunt for individual components or stitch together incompatible systems from different vendors. Google has integrated the hardware, models, orchestration, and interfaces into one cohesive unit. This reduces the time spent managing infrastructure and allows developers to focus on building applications rather than maintaining the stack.
